CS Events

Qualifying Exam

Representative Learning Enabled Efficient Provenance Data Storage


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Thursday, February 09, 2023, 04:30pm - 06:30pm



Recent cyberattacks, such as Advanced Persistent Threats (APTs), are becoming more advanced and sophisticated, targeting multiple operational sectors and lasting longer. Security analysts analyze the system object/subject provenance information in a log or graph to discover the source and ramifications of an attack. Due to the rapid growth of modern computing infrastructure size, software systems are generating more and more provenance data every day. As a result, storing and querying such large-sized provenance data is becoming more challenging. Existing systems are inefficient, with high storage and querying costs. In this talk, I will present our novel, efficient provenance data storage systems motivated by representative learning and novel lossless data compression techniques. Our systems use 25.9 times less storage space and boost up to 99.6% faster queries than existing systems.

Speaker: Hailun Ding

Location : CoRE 301


Professor Shiqing Ma (Advisor)

Professor Dong Deng

Professor Sudarsun Kannan

Professor Abdeslam Boularias

Event Type: Qualifying Exam

Abstract: See above


Rutgers University

School of Arts & Scienes

Department of Computer Science

Contact  Professor Shiqing Ma